Papers › aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception

aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception

17 Nov 2022arXiv:2211.09445archive 2025-07-28

Tamás Matuszka, Iván Barton, Ádám Butykai, Péter Hajas, Dávid Kiss, Domonkos Kovács, Sándor Kunsági-Máté, Péter Lengyel, Gábor Németh, Levente Pető, Dezső Ribli, Dávid Szeghy, Szabolcs Vajna, Bálint Varga

Autonomous driving is a popular research area within the computer vision research community. Since autonomous vehicles are highly safety-critical, ensuring robustness is essential for real-world deployment. While several public multimodal datasets are accessible, they mainly comprise two sensor modalities (camera, LiDAR) which are not well suited for adverse weather. In addition, they lack far-range annotations, making it harder to train neural networks that are the base of a highway assistant function of an autonomous vehicle. Therefore, we introduce a multimodal dataset for robust autonomous driving with long-range perception. The dataset consists of 176 scenes with synchronized and calibrated LiDAR, camera, and radar sensors covering a 360-degree field of view. The collected data was captured in highway, urban, and suburban areas during daytime, night, and rain and is annotated with 3D bounding boxes with consistent identifiers across frames. Furthermore, we trained unimodal and multimodal baseline models for 3D object detection. Data are available at \url{https://github.com/aimotive/aimotive_dataset}.

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bev_transform aimotive/mm_training/dataset/nusc_mv_det_dataset.py community (archive-listed) unverified MIT (permissive) · 75bd9e91eab5963b · report
create_trainer aimotive/mm_training/exps/mm_training_aim.py community (archive-listed) unverified MIT (permissive) · 8b1dc97beb358b74 · report
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Tasks

3D Object DetectionAutonomous DrivingAutonomous VehiclesMultimodal Deep LearningObject Detectionobject-detection

Datasets

Introduced by this paper, per the archive.

aiMotive Dataset

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Object Detection aiMotive Dataset Lidar-Radar-Camera BEV AP@0.3 Highway 0.762 #1 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar-Camera BEV AP@0.3 Night 0.730 #1 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar-Camera BEV AP@0.3 Rain 0.423 #1 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar-Camera BEV AP@0.3 Urban 0.644 #1 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar BEV AP@0.3 Highway 0.757 #2 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar BEV AP@0.3 Night 0.754 #2 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar BEV AP@0.3 Rain 0.568 #2 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar BEV AP@0.3 Urban 0.630 #2 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar BEV AP@0.3 Highway 0.741 #3 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar BEV AP@0.3 Night 0.766 #3 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar BEV AP@0.3 Rain 0.517 #3 of 3 Archive leaderboard report
3D Object Detection aiMotive Dataset Lidar-Radar BEV AP@0.3 Urban 0.638 #3 of 3 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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